Sponsored advertising is a large and dynamic business segment with more than $55 billion spent in 2014. The resulting ecosystem of sponsored advertising includes measurement for potential value of targets (teams, celebrity, retail, stadium spaces) and actual value as measured by “earned viewership” or promotion of the advertising brand. Harvesting of user generated content for displaying or content marketing is another business segment enabled by logo recognition systems. Additionally “competitive brand intelligence” of all media content including online videos, broadcast or streaming video, social images and outdoor display is another use case for more accurate logo recognition systems. Other applications include measurement of product placement within stores, detection and localization of products in retail aisles for a better shopping experience and to provide information for retail management. Additionally, other applications include logistics and industrial applications.
However, current solutions for logo recognition have various limitations. One constraint is time and cost to train a system to recognize new logos due in part to the effort to collect large numbers of trainable images. Another limitation is the accuracy to detect various types of logos in the presence of significant warp, occlusion, blur and varying lighting conditions. Another limitation of general current solutions is a weakness in detecting tiny and often distorted logos on cloth, such as logos located on banners and apparel. Another weakness of such systems is the limited number of logos that can be recognized which is often limited due to accuracy of both current feature detectors that use bag of words methods and learning methods such as neural network classifiers.